Within the coming years it is expected that PV installations could be established on every possible surface and terrain, within the urban environment. Due to the complex morphology of buildings in urban environments,systems will likely be more susceptible to partial shading compared to other conventional PV systems. In particular bifacial PV modules are highly susceptible to shading since they rely on irradiance on both the front and the back surface. To better estimate the irradiance received by such systems, particularly in urban environments, much research is conducted to develop fast and accurate simulation tools. The research described in this report investigated the different simulation frameworks that have been developed for modeling bi-facial PV systems, and develop a new simulation framework capable of simulating irradiance within urban environments. Available models capable of simulating rear irradiance differ in input variables considered,simulation time required and accuracy of predictions. Empirical models, for example, can result in inaccurate predictions since not all variables affecting rear irradiance are considered. Only the 3D view factor, back-ward and forward ray tracing methods fulfill the requirements to simulate the backside irradiance/irradiation when the aim is to perform simulations in more complex urban environments. Out of the existing simulation models tested, the backward ray tracing model performed within the Radiance software proved to be the fastest simulation tool for modeling yearly irradiation or a single irradiance measurement incident under free horizon conditions. Time of use (TOU) simulations, however, results in longer simulation time for backward ray tracing performed in Radiance, since a ray tracing simulation at each time instance is required. To calculate the irradiance a receiving surface receives in an urban environment a method is worked out based on view factors and ray casting. Within the software Rhinoceros a CAD design of the surrounding environment is created, while the plug-in Grasshopper is used for the ray casting and mathematical calculations. Through a series of sanity checks, it was determined that the developed methods are reliable for calculating irradiance/irradiation when the aim is to perform simulations in more complex urban environments. It was also identified how different sky models can result in large differences in irradiance simulated. Sky models such as Isotropic, Hay and Davis or simplified Perez underestimates the irradiance, when receiving surfaces are tilted in comparison with the Perez luminance distributed sky model. The model was validated using monitoring station measurements and compared with simulations performed with other ray tracing models. DHI, DNI measurements obtained from the Solys 2 are used for replicating the irradiance measured at the dual-axis and single-axis tracker. Since their orientation was fixed throughout the measurement period they are referred to as POA 1 and POA 2 respectively. With POA 1 and 2 having a 90 and 30 degree tilt respectfully and an azimuth of 67 and 180 degree respectfully. Making POA 1 the front/back side of a typical (bifacial) east-west configuration and POA 2 the front of a tilted (bifacial) module. Two measurement days are considered, a fully overcast day and a clear sunny day. For the overcast day, an relative RMSE value of 23.09% and 11.7% are achieved for POA 1 and 2. For both cases the irradiation was mostly underestimated, considering the negative MBE and positive MAE. On the clear sunny day, relative RMSE values of 20.35% and 5.26% are achieved for POA 1 and 2. The model again mostly underestimates on the sunny day. A simple DHI correction with the factor 1 divided over the SVF at the Solys 2 is performed in order to investigate the impact of potentially corrupted DHI measurements on the irradiance simulations. With relative RMSE value of 19.96% and 5.2% recorded for POA 1 and 2 on the overcast day. While on the sunny day relative RMSE values of 19.38% and 3.77% are achieved for POA 1 and 2 respectively. Only slightly changing the model predictions. When compared to ray tracing models the model performs slightly better than the forward ray tracing model. A possible reason why the forward ray tracing was underestimated was proposed to be due too the small aim area used. However increasing the aim area would require a larger number of rays to maintain the same accuracy which results in longer simulations.Possible improvements to the model could be, adding reflected irradiance term on reflecting surfaces and the Perez luminance distribution sky model.